「collect」の検索結果

SurrealDB MCP for AI agents: built-in server (SurrealDB 3.1+ `surreal mcp`) and standalone surrealmcp (surrealdb/surrealmcp v0.4.0). Part of the surreal-skills collection.

日本語の概要は準備中です。原文の説明を表示しています。

Nuxt Content v3 Git-based CMS for Markdown/MDC content sites. Use for blogs, docs, content-driven apps with type-safe queries, schema validation (Zod/Valibot), full-text search, navigation utilities. Supports Nuxt Studio production editing, Cloudflare D1/Pages deployment, Vercel deployment, SQL storage, MDC components, content collections.

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Implements efficient API pagination using offset, cursor, and keyset strategies for large datasets. Use when building paginated endpoints, implementing infinite scroll, or optimizing database queries for collections.

日本語の概要は準備中です。原文の説明を表示しています。

Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple sessions.

日本語の概要は準備中です。原文の説明を表示しています。

Create or update a complete repository skill from a user's idea, including the workflow instructions, references, scripts or assets, agent metadata, skill-card artwork, cinematic banner artwork, README links, discovery metadata, and validation. Use when the user asks to create a new skill, add a skill to this collection, turn a workflow into a reusable skill, or make a skill's documentation and artwork consistent with the repository.

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Generate comprehensive marketing analytics reports by collecting KPIs, analyzing trends, and delivering actionable insights with attribution modeling and funnel analysis. Use when the user requests analytics reporting or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert High-Performance Computing Specialist. Use when a task calls for High-Performance Computing Specialist judgment. Reasons from NUMA topology and hybrid MPI+OpenMP+CUDA decomposition through Slurm fairshare/backfill job design, strong/weak scaling (Amdahl/Gustafson), Darshan/mpiP/Nsight profiling, and parallel HDF5/MPI-IO on Lustre while treating I/O storms, collectives bottlenecks, and rank-binding mistakes as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Anatomist. Use when a task calls for Anatomist judgment. Reasons from homology, EPB, and von Baer principles through gross dissection, diceCT/μCT/MRI pipelines, UBERON–PATO EQ annotation, MorphoSource/oVert digitization, geometric morphometrics, and NAV/TA2 nomenclature while treating fixation shrinkage, segmentation artifacts, landmark homology error, and collection bias as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Search videos, analyze channel profiles, track live streams, and research content engagement on WeChat Channels (Video Accounts). Covers video search, channel profiling, live stream monitoring, comment analysis, and content collections.

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Research and collect social proof — testimonials, case studies, user reviews, social mentions, and community endorsements across platforms. Useful for marketing teams building trust content, landing pages, and sales collateral from authentic customer voices.

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Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

日本語の概要は準備中です。原文の説明を表示しています。

CesiumJS entities and data sources - Entity, EntityCollection, DataSource, GeoJsonDataSource, KmlDataSource, CzmlDataSource, Graphics types, PathGraphics, PathMode, Visualizers. Use when adding points, labels, models, polygons, polylines, or time-segmented paths, loading GeoJSON/KML/CZML/GPX data, or working with the high-level Entity API.

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CesiumJS imagery layers - ImageryProvider, ImageryLayer, ImageryLayerCollection, WMS, WMTS, Bing, OpenStreetMap, ArcGIS, Mapbox, tile discard policies. Use when adding or swapping base map layers, configuring imagery providers, layering multiple map sources, or creating split-screen imagery comparisons.

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Validate that analytics and marketing tracking fire CORRECTLY: GA4/GTM dataLayer events, Meta/TikTok/LinkedIn pixels, and ad-tech tags. Covers building a tracking plan as the contract, intercepting collect-endpoint beacons and dataLayer.push in Playwright, asserting event name + params + values + timing + de-duplication, Consent Mode v2 gating, CI regression gating, and news-media events (article-view, scroll-depth, paywall). Use when: "test analytics tracking," "GA4 event test," "verify the pixel fires," "dataLayer test," "tracking plan," "Meta Pixel dedup," "scroll-depth tracking test," "gate tracking in CI." Not for: whether tracking is ALLOWED to fire under consent law (GDPR/CMP) — that is compliance-testing; this skill checks the data is CORRECT. SEO meta tags / structured data — out of scope. Related: compliance-testing, playwright-automation, api-testing, qa-project-context.

日本語の概要は準備中です。原文の説明を表示しています。

Guides God Committee members through consensus-building for collective decisions. Use for proposals, voting, and disagreement resolution. Triggers on: consensus, voting, proposal, committee decision.

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Define monitoring strategy, metrics collection, and alerting thresholds during PRD v0.8 Deployment & Ops. Triggers on requests to set up monitoring, define alerts, or when user asks "what should we monitor?", "alerting strategy", "observability", "metrics", "SLOs", "dashboards", "monitoring setup". Outputs MON- entries with monitoring rules and alert configurations.

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Establish channels and processes for capturing and processing post-launch feedback during PRD v0.9 Go-to-Market. Triggers on requests to set up feedback systems, capture user input, or when user asks "how do we collect feedback?", "feedback loop", "user research", "post-launch feedback", "customer feedback", "NPS", "voice of customer". Outputs CFD- entries specialized for post-launch feedback capture.

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Collect diverse opinions on technical topics from developer communities. Use for "developer reactions", "community opinions" requests. Aggregates Reddit, HN, Dev.to, Lobsters, ProductHunt, etc.

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Guides a founder from real decisions to a short set of written company values that people can act on: collects incidents, tests each candidate value, writes it as a trade-off with behaviors and a story, and wires it into hiring, feedback and promotion. Use when someone asks to "define our company values", "write a values document", "our values are generic, fix them", "turn our values into interview questions", "what should our culture be before we hire", or wants to check whether the team lives the values it has. Produces VALUES.md, an evidence log and an interview kit.

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Collect and manage product feedback with Canny. Use when a user asks to set up a feature request board, prioritize product feedback, build a public roadmap, or let users vote on features.

日本語の概要は準備中です。原文の説明を表示しています。

Assists with building content-driven websites using Astro's island architecture. Use when creating static sites, blogs, documentation, or marketing pages that ship zero JavaScript by default. Trigger words: astro, static site, island architecture, content collections, SSG, hybrid rendering, astro components.

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Aceternity UI is a collection of animated React components (3D cards, spotlight, background beams, moving borders, wavy backgrounds) built with Tailwind CSS and the motion library, installed into your project as source through the shadcn CLI. Use when someone asks for "animated hero section", "3D tilt card", "spotlight effect", "moving border button", "Aceternity component", or "glowing background" in a React or Next.js app.

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Expert at making systems observable and debuggable. Covers structured logging, metrics collection, distributed tracing, error tracking, and alerting. Knows how to find the needle in the haystack when production breaks at 3 AM. Use when "observability, logging, metrics, tracing, monitoring, error tracking, Sentry, Datadog, OpenTelemetry, debugging production, observability, logging, metrics, tracing, monitoring, sentry, prometheus, opentelemetry" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。